*****COURSES ARE SUBJECT TO CHANGE*****
Teaches basic numerical methods for numerical linear algebra and, thus, the solution of ordinary differential equations (ODEs) and partial differential equations (PDEs). Covers LU, Cholesky, and QR decompositions; eigenvalue search methods (QR algorithm); singular value decomposition; conjugate gradient method; Runge-Kutta methods; error estimation and error control; finite differences for PDEs; stability, consistency, and convergence. Basic knowledge of computer programming is needed. Enrollment restricted to graduate students or permission of instructor.
5 Credits
Year | Fall | Winter | Spring | Summer |
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2014-15 |
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2013-14 |
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2012-13 |
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2011-12 |
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2010-11 |
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2009-10 |
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2008-09 |
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2007-08 |
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2006-07 |
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2005-06 |
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